Use cases

What it actually does, on an ordinary Tuesday.

Not capabilities. Situations, and what happens in each.

A filing lands at 4:02pm

Most of them mean nothing to you. LyraMind checks whether this one touches any assumption behind any position you hold. If it does not, it goes quietly into the timeline and nobody is interrupted. If it does, an investigation runs: gather the evidence, then actively search for the evidence that argues the other way, because an investigation that only looked for support found support.

Three sources say the same thing

You get one item, not three. One assumption under pressure is one decision to make, however many documents argued for it, and every triggering document stays attached, because "five filings say this" is stronger than one and you should be able to see that.

An analyst changes their mind

The record captures it: who, when, on what evidence, and what they moved from. A year later, when the outcome is known, that is the only way to answer whether the change was made early or late.

A management commitment stops being mentioned

Nobody announces it. It simply is not in this quarter's script. LyraMind carries the prior ledger forward and reports what fell out, the difference between "we withdrew that target" and silence.

A target resolves

FY27 cash conversion was promised above 90% and came in at 76%. The comparison is arithmetic, done in code, never by a model. Then every decision that rested on that assumption is re-examined, and the firm learns something about itself.

What none of these have in common: a chatbot. LyraMind is not a faster way to read documents. It is a record of why you decided something, kept alive until the outcome is in.

Tell us what you're deciding.

We work with a small number of firms at a time.

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